QualityPrompts

Quick Use and Evaluation of Prompting Techniques

CommonProductProductivityNatural Language ProcessingMachine Learning

QualityPrompts is a Python plugin implementing 58 distinct prompting techniques sourced from research by institutions like OpenAI and Microsoft. It assists users in rapidly constructing and evaluating their prompts by providing a few illustrative examples. The plugin notably boosts accuracy in tasks like solving mathematical problems and is user-friendly and easily integrable.

Install the Quality Prompts plugin using the pip command.
Compose the essential components of your prompt.
QualityPrompts searches and utilizes only a limited number of examples relevant to the user's query.
Invoke one of the various prompting techniques to strengthen the prompt's effectiveness.
Includes System2Attention
which aids in clarifying the given context.
Includes Tabular Chain of Thought Prompting
encouraging the language model to think step-by-step and record each step's process and result.

QualityPrompts is designed for developers and researchers building and evaluating language model prompts. It empowers them to enhance model accuracy and efficiency through a rich repository of prompting techniques
particularly beneficial in natural language processing and machine learning tasks.

Developers use QualityPrompts to refine their chatbot's conversational abilities.
Researchers leverage the plugin to assess the performance of different prompting techniques on specific tasks.
Educators utilize QualityPrompts to teach students how to construct effective language model prompts.

Step 1: Install the Quality Prompts plugin using the pip command.
Step 2: Read the documentation to understand the diverse prompting techniques and their application scenarios.
Step 3: Write your prompt
including context and the question.
Step 4: Select and apply a prompting technique from QualityPrompts.

Visit

QualityPrompts Visit Over Time

Monthly Visits

503747431

Bounce Rate

37.31%

Page per Visit

5.7

Visit Duration

00:06:44

QualityPrompts Visit Trend

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QualityPrompts

QualityPrompts Visit Over Time

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